The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Design of Optimized Fuzzy Controller for Rotary Inverted Pendulum System Using Differential Evolution

차분진화 알고리즘을 이용한 회전형 역 진자 시스템의 최적 퍼지 제어기 설계

  • Received : 2010.07.08
  • Accepted : 2010.09.19
  • Published : 2011.02.01
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Abstract

In this study, we propose the design of optimized fuzzy controller for the rotary inverted pendulum system by using differential evolution algorithm. The structure of the differential evolution algorithm has a simple structure and its convergence to optimal values is superb in comparison to other optimization algorithms. Also the differential evolution algorithm is easier to use because it have simpler mathematical operators and have much less computational time when compared with other optimization algorithms. The rotary inverted pendulum system is nonlinear and has a unstable motion. The objective is to control the position of the rotating arm and to make the pendulum to maintain the unstable equilibrium point at vertical position. The output performance of the proposed fuzzy controller is considered from the viewpoint of performance criteria such as overshoot, steady-state error, and settling time through simulation and practical experiment. From the result of both simulation and practical experiment, we evaluate and analyze the performance of the proposed optimal fuzzy controller from the comparison between PGAs and differential evolution algorithms. Also we show the superiority of the output performance as well as the characteristic of differential evolution algorithm.

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References

  1. H. J. Lee, J. B. Park and G. Chen, "Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties," IEEE Trans. on Syst., Vol. 9, No. 2, pp. 369-379, 2001.
  2. H.-N. Wu and K.-Y. Cai, "Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations," Information Sciences Vol. 177, Issue 6, pp. 1509-1522, 2007. https://doi.org/10.1016/j.ins.2006.07.031
  3. Adcock TA. What is fuzzy logic? An overview of the latest control methodology. TI Application Report, January; p. 1-7. 1993.
  4. Sugeno M, editor. Industrial applications of fuzzy control. Amsterdam: North-Holland; 1985.
  5. 오성권, "C 프로그래밍에 의한 퍼지모델 및 제어시스템", 내하출판사., 2002.
  6. C. C. Lee, "Fuzzy Logic in Control Systems: Fuzzy Logic Controller - part I and part II," IEEE Trans. on Syst., Man Cybern., vol. 20, pp. 404-435, 1990. https://doi.org/10.1109/21.52551
  7. L. Wang, "Stable and Optimal Fuzzy Control of Linear Systems," IEEE Trans. on Fuzzy Syst. vol. 6, no.1, pp.137-143, 1998. https://doi.org/10.1109/91.660813
  8. S.-K. Oh, W. Pedrycz, S.-B. Rho and T.-C. Ahn, "Parameter estimation of fuzzy controller and Its application to inverted pendulum" Engineering Applications of Artificial Intelligence, vol. 17, Issue 1, February 2004, Pages 37-60. https://doi.org/10.1016/j.engappai.2003.12.003
  9. K. Passino i S. Yurkovich, "Fuzzy Control", Addison-Wesley Longman, Ohio 1998.
  10. Zhen-yu Zhao, Massayoshi Tomizuka, Satoru Isaka. "Fuzzy Gain Scheduling of PID Controllers" IEEE Transactions on systems, man and Cybernetic. Vol23, No.5. Sep./Oct. 1993.
  11. Li Zheng. " A Practical Guide to Tune of PI Like Fuzzy Controllers." IEEE. 1992
  12. R. Ortega, M. W. Spong, F. Gomez-Estern, and G. Blankenstein, "Stabilization of a class of underactuated mechanical systems via interconnection and damping assignment," IEEE Transactions on Automatic Control, vol. 47, no. 8, pp. 1218-1233, Aug 2002. https://doi.org/10.1109/TAC.2002.800770
  13. J. J. Jung, T. H. LEE "Global Optimization Using Differential Evolution Algorithm", KIEE The Korean Society of Mechanical Engineers, vol. 27, no. 11, pp. 1809-1814, 2003 https://doi.org/10.3795/KSME-A.2003.27.11.1809
  14. Price, K, "Differential evolution vs. the contest functions of the 2nd ICEO," Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, pp. 153-157, 1997.
  15. Storm, R., "Ont the usage of differential evolution for function optimization," Proceedings of the 1996 North American Fuzzy Information Processing Society (NAFIPS), IEEE Press, pp, 519-523, 1996.
  16. 정재준, 이태희, "차분진화 알고리듬을 이용한 전역최적화", 대한기계학회, 대한기계학회 논문집 A권 제27권 제11호, pp. 1809-1814, 2003.
  17. Sung-Kwun. Oh, Seung-Hyun. Jung, W. Pedrycz, "Design of optimized fuzzy cascade controllers by means of Hierarchical Fair Competition-based Genetic Algorithms", Expert Systems with Applications, Volume 36, Issue 9, pp, 11641-11651, 2009 https://doi.org/10.1016/j.eswa.2009.03.027